<mock-offended>Sides? Me? I'm too busy being a geek here to have a side!</mock-offended> More seriously, I sometimes like to see if I can redefine the sides in a discussion in the hope that it might provide a way forward without anyone having to lose face. That, and the fact that I just like analysing things...
If I had to pick a side; well, I'd say there's more to be gained from engaging in excessive analysis and then being sceptical about the results of said analysis, than in being overcautious about how much analysis you do at all. Consider how science is meant to work (Awooga! Gross oversimplification incoming!): you do some analysis, come up with an idea, but you only accept it when you find that the experiments agree with your analysis.
As for your second sentence; well, you've got the core of a good point there, but I think you might need a bit more work on how you present it.
(Potted summary of fuzzy logic, BTW:
Long, skippable version: you know how you can do all of that boolean stuff where 1 is true and 0 is false? Fuzzy logic extends that so you can have 0.6 or 0.001. Some mathematicians have been able to prove that some sorts of fuzzy logic have all sorts of desirable properties in common with normal logic, but the jury's still out on whether it's possible to do anything useful with it that you couldn't do better with normal logic and some probability, and it's entirely unclear what relation (if any) it has to what the brain does or what sentences mean.
Short version: it's one of those things for dealing with uncertainty and in particular ambiguity that AI types like to argue about.)
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<mock-offended>Sides? Me? I'm too busy being a geek here to have a side!</mock-offended> More seriously, I sometimes like to see if I can redefine the sides in a discussion in the hope that it might provide a way forward without anyone having to lose face. That, and the fact that I just like analysing things...
If I had to pick a side; well, I'd say there's more to be gained from engaging in excessive analysis and then being sceptical about the results of said analysis, than in being overcautious about how much analysis you do at all. Consider how science is meant to work (Awooga! Gross oversimplification incoming!): you do some analysis, come up with an idea, but you only accept it when you find that the experiments agree with your analysis.
As for your second sentence; well, you've got the core of a good point there, but I think you might need a bit more work on how you present it.
(Potted summary of fuzzy logic, BTW:
Long, skippable version: you know how you can do all of that boolean stuff where 1 is true and 0 is false? Fuzzy logic extends that so you can have 0.6 or 0.001. Some mathematicians have been able to prove that some sorts of fuzzy logic have all sorts of desirable properties in common with normal logic, but the jury's still out on whether it's possible to do anything useful with it that you couldn't do better with normal logic and some probability, and it's entirely unclear what relation (if any) it has to what the brain does or what sentences mean.
Short version: it's one of those things for dealing with uncertainty and in particular ambiguity that AI types like to argue about.)